class_docstr: Raised when an operator is unsupported by the exporter.
class_docstr_tok: ["Raised","when","an","operator","is","unsupported","by","the","exporter","."]
code: def __init__(
      self, name: str, version: int, supported_version: Optional[int]
  ):
      if supported_version is not None:
          diagnostic_rule: diagnostics.infra.Rule = (
              diagnostics.rules.operator_supported_in_newer_opset_version
          )
          msg = diagnostic_rule.format_message(
              name, version, supported_version
          )
          diagnostics.diagnose(
              diagnostic_rule, diagnostics.levels.ERROR, msg
          )
      else:
          if name.startswith(("aten::", "prim::", "quantized::")):
              diagnostic_rule = (
                  diagnostics.rules.missing_standard_symbolic_function
              )
              msg = diagnostic_rule.format_message(
                  name, version, _constants.PYTORCH_GITHUB_ISSUES_URL
              )
              diagnostics.diagnose(
                  diagnostic_rule, diagnostics.levels.ERROR, msg
              )
          else:
              diagnostic_rule = (
                  diagnostics.rules.missing_custom_symbolic_function
              )
              msg = diagnostic_rule.format_message(name)
              diagnostics.diagnose(
                  diagnostic_rule, diagnostics.levels.ERROR, msg
              )
      super().__init__(msg)
  
file_path: pytorch/torch/onnx/errors.py
imports: from __future__ import annotations
  import textwrap
  from typing import Optional
  from torch import _C
  from torch.onnx import _constants
  from torch.onnx._internal import diagnostics
label_desc: Use image node_id 1 to create a new UnsupportedOperatorError object from inherited base classes: OnnxExporterError with example: obj = UnsupportedOperatorError(name, version, supported_version)